Capability Maturity Model (CMM) method for assessing the performance of low-carbon city practice

Carbon emissions are considered as major factor affecting sustainable urban development. Cities have been promoting low carbon city (LCC) strategies to reduce carbon emissions and various methods have been introduced to assess the performance of LCC strategies. However, most of the existing assessment methods focus on overall LCC performance at city level, but the effects of individual dimensions like industrial structure and energy efficiency are ignored. The research question in this study therefore is whether an alternative method can be established to measure both the overall and dimensional LCC performance. This paper introduces a method for assessing LCC performance by using Capability Maturity Model (CMM), which is called LCC-CMM. The proposed method of LCC-CMM can help identify LCC maturity grade through assessing the performance of individual LCC dimensions which contributes to overall performance. There are four procedures in applying LCC-CMM, including to identify the Key Process Areas (KPAs) in the context of LCC, denoted as LCC-KPAs, to define the indicators for measuring the performance of LCC-KPAs, to calculate the performance score for each LCC-KPA, and to define criteria for specifying different grades of LCC capability maturity. The proposed method is proven effective through a case demonstration. The method can help policy makers to identify weak areas in LCC practice and introduce tailor-made policy measures to improve the weak areas.

Automated summary

Carbon emissions are a major factor affecting sustainable urban development, and cities are implementing low carbon city strategies to reduce emissions. However, existing assessment methods often overlook the effects of individual dimensions like industrial structure and energy efficiency. This study proposes a new method, LCC-CMM, to assess both overall and dimensional LCC performance, helping policymakers identify weak areas and improve them with tailored measures.